<i>In vitro</i> Antioxidant and Antimicrobial Effects of <i>Ceratostigma plumbaginoides</i>
Bibliographic record
Abstract
Bioactive compounds, including phenols, flavonoids, and tannins, were quantified in leaves, stems and roots of methanol, n-butanol, diethyl ether and n- hexane extracts of Ceratostigina plumbaginoides Bunge. (Plumbaginaceae) ornamental plants. The antioxidant capacity was measured by the DPPH and linoleic acid assays. The total bioactive compounds, as well as the antioxidant capacities, were the highest in the leaves compared with stems and roots. The -methanolic, n-butanol, diethyl ether and n-hexane leaf extracts varied in their antibacterial and antifungal activities. In general, the most sensitive bacterium to leaf extracts was Bacillus cereus and the most resistant was Staphyllococcus aureus, while the most sensitive fungus was Aspergillusflavus and the most resistant one was Penicillium ochrochloron. As the methanolic leaf extract was the most active, it was subjected to column chromatography and two compounds were isolated and identified as 1 (5-hydroxy-2-methyl-1,4-naphthoquinone / plumbagin) and 2 (3,3'-biplumbagin). Compounds 1 and 2 showed the highest antibacterial and antifungal activities compared with other extracts tested. The MIC and MBC values for the most active compound 1 were in the range of 0.001 - 0.09 and 0.004 - 0.21 mg mL⁻¹, while MIC and MFC were determined as 0.001 - 0.11 and 0.002 - 0.19 mg mL⁻¹, respectively. The isolated compounds and leaf extracts showed also equal or higher antimicrobial activities compared with antibiotics/commercial reagents which indicate that the plant might be useful for drug development. This is the first report on the antibacterial and antifungal activities, as well as the antioxidant properties of the tested plant parts and isolated compounds.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".